PPG.EGPSA/ITEGAM
URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/1
A comunidade dispõe da produção técnica e científica do Programa de Pós-graduação em Engenharia, Gestão de Processos, Sistema e Ambiental (PPG.EGPSA) do Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM), fruto da atividade de pesquisa e desenvolvimento (P&D). É possível acessar os trabalhos de conclusão do programa de pós-graduação, artigos e livros vinculados a pesquisa, desenvolvimento, inovação e extensão.
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Resultados da Pesquisa
Item Smart energy: aplicação do sistema fotovoltaico utilizando algoritmos genéticos para tomada de decisão na Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) WASCHINGTON, Adriana Carneiro; SILVA, Simone daThe global energy transition and the need for energy efficiency in industrial environments are driven by the search for sustainability and the reduction of environmental impacts. This work addresses the application of genetic algorithms in the management of photovoltaic systems within the context of Industry 4.0, highlighting the concept of Smart Energy. The main objective is to investigate the benefits and impacts of this approach on energy efficiency, environmental sustainability, and the reduction of operating costs at the Manaus Industrial Estate (PIM). To achieve the objectives, methods based on computer simulation and analysis of real cases were used. The research included the modeling and development of genetic algorithms capable of optimizing variables such as energy generation, storage, and consumption in photovoltaic systems. Data was collected based on local climatic conditions, energy demand profiles, and industrial operating parameters. The results indicated that the genetic algorithms enabled significant gains in energy efficiency, with an average reduction of 20% in energy waste and 15% in operating costs. In addition, the model developed proved to be effective in adapting to climate variations and industrial demands, reducing dependence on non-renewable sources and greenhouse gas emissions. The conclusion is that integrating photovoltaic systems with genetic algorithms is a promising solution for energy management in Industry 4.0, promoting sustainability and industrial competitiveness, especially in regions with high solar incidence like the Amazon. The research highlights the relevance of technological innovation in the transition to a low-carbon economy.Item Smart energy: application of the photovoltaic system using genetic algorithms for decision making in industry 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) OLIVEIRA, Adriana Waschington Carneiro de; SILVA, Simone da; ALMEIDA, Anderson Alexandre Silva de; MONTEIRO, Odilon Bentes; RIBEIRO, Paulo Francisco da Silva; NASCIMENTO FILHO, Alarico Gonçalves do; LEITE, Jandecy CabralThe growing demand for sustainable solutions and the digitalization of industrial processes have driven the adoption of photovoltaic systems and advanced decision-making technologies. In the context of Industry 4.0, where automation and artificial intelligence are fundamental, these systems stand out as a clean energy alternative, promoting savings and reducing pollutant emissions. This study aims to develop a photovoltaic energy control model that uses genetic algorithms to optimize energy efficiency in industrial environments, reducing costs and dependence on non-renewable sources. The methodology included the computational modeling of a photovoltaic system and the application of genetic algorithms to optimize parameters such as panel angle and operating hours, adapting the system in real time to variable consumption and generation conditions. The results showed that the use of genetic algorithms increased the system's efficiency by up to 20% compared to traditional methods, as well as minimizing consumption from the electricity grid at peak times. This study reinforces the importance of artificial intelligence in optimizing renewable resources, contributing to energy efficiency and sustainability in Industry 4.0.Item Smart Energy: aplicação do sistema fotovoltaico utilizando algoritmos genéticos para tomada de decisão na indústria 4.0(Instituto Nacional da Propriedade Industrial (INPI), 2024) OLIVEIRA, Adriana Waschington Carneiro de; SILVA, Simone daThis document certifies the registration of the "Smart Energy" software, which employs genetic algorithms for decision-making in the context of Industry 4.0. The application focuses on photovoltaic systems, aiming to optimize industrial processes through advanced computational techniques.Item Algoritmo Genéticos aplicado à Qualidade de Energia - DASHBOARD(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy CabralRegistration of a computer program entitled "Genetic Algorithms Applied to Power Quality - DASHBOARD," valid for 50 years from January 1st following the publication date (12/17/2024). The program was created for specific applications outlined in the technical areas defined by the National Institute of Industrial Property (INPI).